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Record W2626779244 · doi:10.3847/1538-3881/aa79f3

H i Kinematics and Mass Distribution of Messier 33

2017· article· en· W2626779244 on OpenAlexaff
Sié Kam, C. Carignan, L. Chemin, T. Foster, Ed Elson, T. H. Jarrett

Bibliographic record

VenueThe Astronomical Journal · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsDominion Astrophysical ObservatoryUniversité de Montréal
Fundersnot available
KeywordsPhysicsAstrophysicsDark matterHaloGalaxy rotation curveDark matter haloGalaxyMass distributionAstronomyMilky WayVirial mass

Abstract

fetched live from OpenAlex

Abstract A new deep H i survey of the galaxy Messier 33 is presented, based on observations obtained at the Dominion Radio Astrophysical Observatory. We observe a perturbed outer gas distribution and kinematics in M33, and confirm the disk warping as a significant twist of the major axis of the velocity field, although no strong tilt is measured, in agreement with previous work. Evidence for a new low-brightness H i component with anomalous velocity is reported. It harbors a large velocity scatter, as its kinematics both exceeds and lags the rotation of the disk, and leaks in the forbidden velocity zone of apparent counterrotation. The observations also reveal wide and multiple-peak H i profiles that can be partly explained by crowded orbits in the framework of the warp model. Asymmetric motions are identified in the velocity field as possible signatures of a lopsided potential and the warp. The mass distribution modeling of the hybrid H α –H i rotation curve favors a cuspy dark matter halo with a concentration in disagreement with the ΛCDM dark halo mass–concentration relationship. The total mass enclosed in 23 kpc is , of which 11% are stars and gas. At the virial radius of the cuspy halo, the resulting total mass is , but with a baryonic mass fraction of only 2%. This strongly suggests a more realistic radius encompassing the total mass of M33 that is well smaller than the virial radius of the halo, possibly comparable to the size of the H i disk.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.228
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2017
Admission routes1
Has abstractyes

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